Destination Choice Game: A Spatial Interaction Theory on Human Mobility

TL;DR

This paper introduces the Destination Choice Game (DCG), a new spatial interaction model for predicting human mobility fluxes that accounts for congestion and crowding effects, improving accuracy over existing models.

Contribution

The paper presents the DCG, a microscopic decision-making model incorporating crowding effects, and demonstrates its superior predictive performance compared to traditional models.

Findings

DCG outperforms existing models in predicting mobility fluxes.

Gravity model is a special case of the DCG without crowding effects.

DCG is effective across multiple spatial scales from intra-city to intercity.

Abstract

With remarkable significance in migration prediction, global disease mitigation, urban planning and many others, an arresting challenge is to predict human mobility fluxes between any two locations. A number of methods have been proposed against the above challenge, including the gravity model, the intervening opportunity model, the radiation model, the population-weighted opportunity model, and so on. Despite their theoretical elegance, all models ignored an intuitive and important ingredient in individual decision about where to go, that is, the possible congestion on the way and the possible crowding in the destination. Here we propose a microscopic mechanism underlying mobility decisions, named destination choice game (DCG), which takes into account the crowding effects resulted from spatial interactions among individuals. In comparison with the state-of-the-art models, the present one shows more accurate prediction on mobility fluxes across wide scales from intracity trips to intercity travels, and further to internal migrations. The well-known gravity model is proved to be the equilibrium solution of a degenerated DCG neglecting the crowding effects in the destinations.